Amplinth Lending is a front-to-back credit-processing platform for private and commercial banks — advisory to closure, plus a dedicated securities-backed (Lombard) vertical. Twenty-five AI agents do the processing and analysis; deterministic engines run the risk math; and a mandatory human decision gates every credit decision.
Advisory, KYC, underwriting, setup and monitoring run as sequential, disconnected steps — so each one waits on the last, and proving the decision to a regulator means reassembling it after the fact.
The same disciplined Amplinth loop, tuned to credit — agents and deterministic engines do the work; your credit officers, risk officers and committee make every decision.
Borrower applications (portal + public API), documents, KYC / sanctions sources, register lookups and market / custody data — multi-tenant scoping isolates each bank.
25 AI agents extract, spread, score, value collateral and draft memos; deterministic Lombard engines run haircut, LTV, concentration and stress math with no LLM in the path.
Product matches, risk ratings, credit memos, recommended covenants and pricing, early-warning alerts and margin calls — each surfaced as a decision-ready package.
Approvals route through the delegation-of-authority chain; contracts generate and route for signature; monitoring and reviews run on schedule. A human gates every credit decision.
RAROC and EVA per facility and portfolio, plus an immutable audit log and MRM.
Twenty-five AI agents and ~30 route domains span advisory to closure — every module wired and running in code, with a human checkpoint on every credit decision.
Self-service advisory and product matching guide an applicant from business profile to the right product, then convert an advisory record into an application — with borrower management and a borrower customer portal (Apply, Status, Advisor, Dashboard).
Identity / company verification and sanctions / PEP screening (including the Swiss SECO high-risk list); a document-collection agent builds a loan-type-aware checklist and chases outstanding items; classification routes each file to the right extractor.
Vision / LLM extraction turns PDFs into structured financials; a spreading agent populates standardised statements, computes ratios, and records a human sign-off on the spread before it feeds the memo.
A risk-scoring agent assigns a preliminary rating; a fraud-detection agent checks document authenticity, anomalies and velocity; a credit-memo agent drafts a structured memo (profile, highlights, risk factors, mitigants, recommended terms) with full version history.
A collateral register and valuation agent value assets from market data; a setup module generates a perfection checklist, records perfection and insurance, and exposes a funding gate; a monitoring agent tracks coverage over the life of the loan.
A covenant-conditions agent recommends and tests covenants per application; risk-based pricing computes RAROC and EVA (Economic Value Added) from PD / LGD / EAD, with pricing variance and repricing recommendations.
A delegation-of-authority chain routes each case to the right approver(s) by exposure, rating and product; policy evaluation checks the application against codified credit policy and lists any breaches before a decision is made.
A contract-generation agent populates offer letters, term sheets and credit agreements with approved terms and multi-language branding; a review agent flags non-standard clauses for legal; CP-tracking and limit-config agents prepare activation.
Covenant monitoring tests on schedule and records breaches and cures; portfolio margin analytics compute risk-adjusted margin / EVA at loan and book level; an early-warning agent detects deterioration for a risk officer to triage.
A periodic-review agent schedules reviews, conducts them with pre-populated financials, tracks history per loan and records a rating decision — turning the annual scramble into a continuous, evidenced process.
A collections agent opens cases, records actions, proposes arrangements and escalates; a workout agent suggests restructuring options (the human approves terms); a closure agent processes payoff, collateral release and archival once a human confirms settlement.
Mandatory HITL checkpoints gate every credit decision; model-risk management registers each agent as a governed model with per-agent metrics and versioning; an immutable audit log records every action — AI processes and analyses; humans review, validate and decide.
Alongside the commercial / SME credit workflow runs a dedicated Lombard vertical for private banking. The math runs on deterministic engines — explicitly LLM-free — for auditability; AI agents handle advisory, assessment and documents around them.
Facilities carry target / warning / margin-call / liquidation LTV bands, currency, base rate, spread and cure / grace periods. A deterministic haircut engine computes the effective haircut per pledged position — base, concentration, currency-mismatch and liquidity overlays — fully auditable, no LLM. LTV, concentration and stress engines drive live analytics (including a −20% stress scenario).
A margin-call state machine drives issuance, cure and escalation as LTV crosses bands, surfaced to the client in the borrower portal. ISIN-level eligibility management and a scheduled re-check (blacklist, asset class, stale prices >30 days) keep pledged positions within policy.
An enhanced-due-diligence path for high-net-worth borrowers runs with its own mandatory human sign-off checkpoint. Lombard-specific advisory, credit-assessment and document agents run the securities-lending path, with valuation, drawdown, reporting and lead services around them.
Live custody / broker feeds and the e-signature provider binding are confirmed per tenant before a specific vendor is named — adapter stubs exist where a live binding isn't yet wired.
Every underwriting-time, accuracy and throughput figure below originates from prospect-bank framework decks and is labelled Modelled or Target — none is a realized client result. The capabilities beneath them are facts, confirmed in the running code.
Genuine front-to-back coverage — advisory to closure, plus Lombard — with a human decision at every credit gate.
Connect Amplinth Lending to your borrower channels, KYC / sanctions sources and market / custody data. Configure products, policy, the DoA matrix and jurisdiction to your tenant — the lifecycle is reusable; the policy and jurisdiction are what we tailor. Operate the governed loop in the cloud, with a mandatory human gate on every credit decision.
Formal certifications (SOC 2 / ISO 27001 / ISO 42001 / GDPR) and named external integrations (custody / broker, e-signature) are confirmed per tenant before publishing as available.
Advisory, KYC, extraction, underwriting, collateral, covenants, pricing, approvals, contracts, monitoring, review and closure — all implemented and wired, not slideware. Most competitors cover a slice.
AI processes and analyses; your credit officers, risk officers and committee review, validate and decide. Mandatory HITL gates, MRM model governance and an immutable audit log make every decision defensible.
Securities-lending math runs on LLM-free, auditable engines that private banks and regulators require — and RAROC / EVA are computed in the pricing path, tying every facility to value.
Book a 30-minute demo on your hardest credit case — watch the agents extract, spread, score and draft the memo, see the Lombard engines run the haircut and LTV, and meet the human gate at every decision.